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Record W2118164433 · doi:10.1079/bjn20061694

Community nutrition programmes, globalization and sustainable development

2006· article· en· W2118164433 on OpenAlexaff
José Carlos Suárez-Herrera

Bibliographic record

VenueBritish Journal Of Nutrition · 2006
Typearticle
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsGlobalizationEconomic growthDeveloping countryContext (archaeology)PopulationPolitical scienceSustainable developmentDemocratizationInternational communityGlobal healthDevelopment economicsPoliticsMedicineEnvironmental healthHealth careEconomicsDemocracyGeography

Abstract

fetched live from OpenAlex

On an international scale, the last seventy-five years have been a period of deep social, economic and political transformation for the developing countries. They have been especially influenced by the international phenomenon of globalization, the benefits of which have been unequally distributed among countries. In this context, the strategies used to improve the general nutritional health of the population of developing countries include broad approaches integrating nutritional interventions in a context of sustainable community development, while valuing the existing relations between fields as diverse as agriculture, education, sociology, economy, health, environment, hygiene and nutrition. The community nutrition programmes are emblematic of these initiatives. Nevertheless, in spite of the increasing evidence of the potential possibilities offered by these programmes to improve the nutritional status and contribute to the development and the self-sufficiency of the community, their success is relatively limited, due to the inappropriate planning, implementation and evaluation of the programmes. In the present article, I attempt to emphasie the importance of community participation of the population of developing countries in the community nutrition programmes within the context of globalization. This process is not only an ethical imperative, but a pragmatic one. It is a crucial step in the process of liberation, democratization and equality that will lead to true sustainable development.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.014
Scholarly communication0.0050.003
Open science0.0010.008
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0080.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.062
GPT teacher head0.380
Teacher spread0.318 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2006
Admission routes1
Has abstractyes

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Same venueBritish Journal Of NutritionSame topicFood Security and Health in Diverse PopulationsFrench-language works237,207